Optimum dispatch of a multi-storage and multi-energy hub with demand response and restricted grid interactions

Integrated energy systems such as multi energy hubs which combines different energy conversion technologies and storage is recently getting popular. These systems possess the potential to integrate distributed renewable energy sources with a minimum impact to the grid. Hence, a number of recent studies have focused on optimizing the operation of energy hubs with simple energy systems. This study focuses on optimizing the dispatch of a multi-energy hub model which includes solar PV (SPV) panels, wind turbines, boiler, Internal Combustion Generator (ICG), Cogeneration plant (CHP), energy storage (heat and electricity). The energy hub is considered to maintain limited interactions with the grid. Interactions with e-mobility is considered as a flexible demand. A detailed energy hub model is developed considering energy interactions among all the aforementioned components. Dispatch strategy is optimized using evolutionary algorithm. Results obtained from the evolutionary algorithm is compared with Particle Swarm Optimization (PSO) algorithm. A detailed analysis is conducted in order to assess the energy interactions within the system. Sensitivity of system components such as storage size, renewable energy capacity etc., grid interactions, and time horizon considered for optimization is subsequently assessed and reported concisely. Results obtained clearly shows choice of dispatch strategy is considerably volatile which makes the operation of the energy hub challenging. This can be mitigated up to a certain level by increasing the capacity of battery bank